uniprot-database

uniprot-database is a skill for Claude Code, Codex from silverstein/claude-scientific-skills-desktop. It costs 66 tokens per session (1,631 once invoked), scanned A, a copy of uniprot-database, MIT.

A direct interface to UniProt, a large database of protein sequences and biological information. It can find proteins, retrieve their sequences, connect identifiers across databases, and return annotations.

In plain words
What is it for?
Use it to search by protein, gene, accession, or organism; download FASTA sequences; map identifiers; and inspect reviewed or unreviewed protein annotations.
Why use it?
It avoids manually looking up protein records and helps keep protein data retrieval consistent in code-based research workflows.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to search by protein, gene, accession, or organism; download FASTA sequences; map identifiers; and inspect reviewed or unreviewed protein annotations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/silverstein/claude-scientific-skills-desktop/uniprot-database
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add silverstein/claude-scientific-skills-desktop --skill uniprot-database
Clone the repo
git clone --depth 1 https://github.com/silverstein/claude-scientific-skills-desktop

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for uniprot-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/silverstein/claude-scientific-skills-desktop/uniprot-database/github.svg)](https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/uniprot-database)
Your own site
<a href="https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/uniprot-database"><img src="https://agentmods.dev/badge/skills/silverstein/claude-scientific-skills-desktop/uniprot-database/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for uniprot-database

Your own site · 80×15
<a href="https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/uniprot-database"><img src="https://agentmods.dev/badge/skills/silverstein/claude-scientific-skills-desktop/uniprot-database.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,631 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 92% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00066 $0.01631
Opus 5 $0.00033 $0.00816
Sonnet 5 $0.00013 $0.00326
Haiku 4.5 $0.00007 $0.00163

Measured 8d ago against content hash 813eea4b47a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

uniprot-database scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/uniprot_client.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- `api_examples.md` - Code examples in multiple languages (Python, curl, R)
Origin

This is a copy

92% identical to uniprot-database — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

corpus/uniprot-database/SKILL.md · 190 lines

How it starts

The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.

UniProt Database

Overview

UniProt is the world's leading comprehensive protein sequence and functional information resource. Search proteins by name, gene, or accession, retrieve sequences in FASTA format, perform ID mapping across databases, access Swiss-Prot/TrEMBL annotations via REST API for protein analysis.

When to Use This Skill

This skill should be used when:

  • Searching for protein entries by name, gene symbol, accession, or organism
  • Retrieving protein sequences in FASTA or other formats
  • Mapping identifiers between UniProt and external databases (Ensembl, RefSeq, PDB, etc.)
  • Accessing protein annotations including GO terms, domains, and functional descriptions
  • Batch retrieving multiple protein entries efficiently
  • Querying reviewed (Swiss-Prot) vs. unreviewed (TrEMBL) protein data
  • Streaming large protein datasets
  • Building custom queries with field-specific search syntax

Core Capabilities

1. Searching for Proteins

Search UniProt using natural language queries or structured search syntax.

Common search patterns:

# Search by protein name
query = "insulin AND organism_name:\"Homo sapiens\""

# Search by gene name
query = "gene:BRCA1 AND reviewed:true"

# Search by accession
query = "accession:P12345"

# Search by sequence length
query = "length:[100 TO 500]"

# Search by taxonomy
query = "taxonomy_id:9606"  # Human proteins

# Search by GO term
query = "go:0005515"  # Protein binding

Use the API search endpoint: https://rest.uniprot.org/uniprotkb/search?query={query}&format={format}

Supported formats: JSON, TSV, Excel, XML, FASTA, RDF, TXT

2. Retrieving Individual Protein Entries

Retrieve specific protein entries by accession number.

Accession number formats:

  • Classic: P12345, Q1AAA9, O15530 (6 characters: letter + 5 alphanumeric)
  • Extended: A0A022YWF9 (10 characters for newer entries)

Retrieve endpoint: https://rest.uniprot.org/uniprotkb/{accession}.{format}

Example: https://rest.uniprot.org/uniprotkb/P12345.fasta

Read the full file on GitHub · 190 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 190 lines · 66 tokens per session scan A 813eea4b47a6

Subscribe to this mod's changes

uniprot-database is a skill published in the GitHub repository silverstein/claude-scientific-skills-desktop (22 stars, last pushed 5mo ago), licensed MIT. It adds 66 tokens to every session and 1,631 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 92% identical to uniprot-database, differing in 7 lines, and is treated as a copy.

Related

Other skills, from other repositories

bio-ortholog-inference

Pull pre-computed ortholog calls from public databases (OrthoDB, Ensembl Compara, OMA browser, eggNOG, PANTHER, KEGG Orthology, HomoloGene) via their REST APIs. Use when orthologs are already curated upstream, when the question is "what is the X ortholog of Y" rather than "how to infer orthology de novo", when…

PKU-YuanGroup/OpenAI4S · 141 tokens

admet_genetic

ADMET-guided genetic molecule optimization workflow from seed SMILES; use when the agent needs to build or run an RDKit/SA-Score/ADMET-AI GA pipeline for molecule optimization, enforce molecule lineage logs, render optimization-history HTML dashboards, and write candidate triage reports.

PKU-YuanGroup/OpenAI4S · 63 tokens

bioprobench

Score an LLM's biological-protocol reasoning on the BioProBench benchmark: protocol QA, step ordering, error detection, protocol generation, and LLM-judged error reasoning; or generate the responses.

PKU-YuanGroup/OpenAI4S · 46 tokens

alphafold2

Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency…

PKU-YuanGroup/OpenAI4S · 117 tokens

bio-alignment-msa-parsing

Parse and analyze multiple sequence alignments using Biopython. Extract sequences, identify conserved regions, analyze gaps, work with annotations, and manipulate alignment data for downstream analysis. Use when parsing or manipulating multiple sequence alignments.

PKU-YuanGroup/OpenAI4S · 52 tokens

bio-causal-genomics-heritability-partitioning

Estimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML…

PKU-YuanGroup/OpenAI4S · 186 tokens